This invention relates to academic analytics, and more particularly to the use of academic analytics to improve student success.
Across the country, institutions of higher education are struggling with problems relating to retention of early career students. The rising cost of tuition, a higher calling for accountability, and the lack of institutional attention to first-year student experiences combine to make retention a devastating factor on the effectiveness of the education being delivered today. The ability to predict student academic performance and retention within higher education has long been a focus of faculty and institutional research. The results of this research have led to the development of admissions formulas, descriptive models, assessment tools, and numerous journal articles.
Accurately predicting academic success and ensuring retention of students has been examined from a number of different directions. One of the earliest applications for predicting academic success was the college admissions process. As the demand for higher education grew, institutions turned to various mathematical models based on high school records and standardized examinations. However, such attempts failed to address the issue of retaining students once they were accepted into an academic institution.
One of the first attempts to explain student retention was made in 1975 by Alexander Astin, who created the Input-Environment-Outcome model to serve as a conceptual framework for analyzing student persistence in studying. The purpose of the model was to assess the impact of various environmental experiences by determining whether students grow or change differently under varying environmental conditions. Astin argued that one must examine the preexisting characteristics prior to entering college (inputs), the environmental factors of the institution (size, student involvement, etc.), and the effects of college (outcomes). In 1991, Astin identified 146 possible input (pre-college) variables including: age, race, high school grades, and reasons for attending college. Astin also identified 192 environmental variables which might influence student success. These were broken into eight classifications: institutional characteristics, students' peer group characteristics, faculty characteristics, curriculum, financial aid, major field of choice, place of residence, and student involvement. The final component of Astin's model was outcomes. Astin identified 82 outcomes including academic cognition, career development, and retention.
Vincent Tinto, another notable researcher in this field since the mid-1970s, also attempted to explain the variables that influence student persistence. Tinto theorized that students enter with a certain set of characteristics that increase or decrease their commitment to and integration into the institution and concluded that greater integration leads to higher retention. In a speech given to the European Access Network in 2002, Vincent Tinto noted that “students are more likely to persist when they find themselves in settings that hold high expectations for their learning, provide needed academic and social support, and actively involve them with other students and faculty in learning.” As researchers have struggled to understand the factors that ensure student retention, the students themselves have changed in ways that undermine the effectiveness of previous research and proposed solutions.
When interacting with a generation that prefers an on-line conversation to a real-life one, there exist challenges with letting students know how they are doing in a class before it is too late for them to change behaviors, especially when failing to change behaviors would result in receiving a D, F, or withdrawal (D/F/W) from the course—final outcomes that generally will not help students persist towards their stated degree objectives. It would seem that this can be easily addressed simply by students taking the time to either meet with their professors on a regular basis or by simply keeping track of the grades they receive and then seeking assistance when needed. Indeed, previous research would suggest this approach. However, students generally are not proactive enough for these behaviors to occur. Despite nearly six decades of research studying the issues of student persistence and retention in higher education, overall retention figures have remained between 45% and 50%. It is clear that major deficiencies exist in the prior art systems, methods, and proposals and the problems are frustrated by the fact that students themselves have changed, as discussed above.